Medical viewing system and method for detecting borders of an object of interest in noisy images

ABSTRACT

The invention relates to a viewing system and a method for detecting an object of interest in a sequence of images (IS). Said object of interest is detected by first locating localizers related to said object of interest and by locating borders (BL) related to said object of interest using the location (LI, LZ) of said localizers. The viewing system according to the invention is able to produce a sequence of enhanced images in which the object of interest is enhanced, to measure some characteristics and to build a three dimensional representation of said object of interest. The viewing system is also able to register and combine said sequence of enhanced images with a sequence of reference images.

FIELD OF THE INVENTION

The invention relates to a viewing system, comprising acquisition meansfor acquiring a sequence of images, detection means for detecting anobject of interest in said sequence of images, and viewing means fordisplaying said sequence of images. The invention also relates to amethod to be used in said system. The invention also relates to amedical examination apparatus coupled to such a system.

The invention finds its application for example in medical imagingsystems for the detection of objects of interest such as stents andartery walls in angiograms.

BACKGROUND OF THE INVENTION

A method for detecting stents in medical images is already known fromthe publication entitled “Deformable Boundary Detection of Stents inAngiographic Images”, by Ioannis Kompatsiaris et alii, in IEEETransactions on Medical Imaging, Vol. 19, no 6, June 2000, pages652-662. This document describes an image processing method fordeformable boundary detection of medical tools, called stents, inangiographic images.

A stenosis is a narrowing of a blood vessel. When a stenosis isidentified in a coronary artery of a patient, a procedure calledangioplasty or Percutaneous Transluminal Coronary Angioplasty (PTCA) maybe prescribed. A basic idea of PTCA is to position a monorail with asmall inflatable balloon within a narrowed section of an artery. Theballoon is inflated in order to push outwards against the wall of thenarrowed artery. This process reduces the narrowing until it no longerinterferes with the blood flow. The balloon is then deflated and removedfrom the artery. In order to avoid re-stenosis to occur, said process isoften followed by a stent implantation. A stent is a surgical stainlesssteel coil that is introduced in the artery on another balloon monorail.The stent is wrapped tightly around the balloon attached to themonorail. Said balloon tipped monorail is introduced into the artery.The inflation of the balloon causes the stent to expand, pressing itagainst the artery wall. The stent, once expanded, can be considered asa permanent implant, which acts like a scaffold keeping the artery wallopen and allowing normal blood flow to occur through the artery. Stentplacement helps many patients avoid emergency heart bypass interventionsand/or heart attacks.

A key step of said procedure is to check whether the stent has beenplaced at the right position of the stenosis and whether it has beensuccessfully expanded. As a matter of fact, clinical problems areassociated with inadequate placement or expansion of the stent.Inadequately expanded stents can locally disrupt blood flow and causethrombosis.

During a PTCA it is possible to observe in real time the area of thestenosis in a sequence of angiographic images, but the precise stentplacement is not easily visible for several reasons:

-   -   the image sequence is rather noisy and its contrast is low due        to the use of a low X-Ray dose,    -   the stent location changes all along the image sequence due to        the influence of cardiac pulses and the patient's breathing.        Studies revealed that, consequently, more than eighty per cent        of stents might be insufficiently dilated despite an apparently        successful deployment in the sequence of angiographic images.        Automatic detection of the stent border could, therefore, help        to achieve a more precise checking of the stent placement.

The method that is disclosed in the cited publication relies on theidentification of the stent in the angiographic images. It comprises thesteps of:

-   -   forming 3D models of stents,    -   deriving a set of 2D models using perspective rules,    -   matching said 2D models with real angiographic images in a        training phase,    -   roughly detecting a stent in an angiographic image using the set        of 2D models and maximum likelihood criteria,    -   refining the borders of the roughly detected stent using an        active contour model.

A drawback of said method is that it presents a calculation load that isactually too heavy for real time processing of a sequence of images inthe intervention phase of stent implantation.

SUMMARY OF THE INVENTION

It is an object of the invention to propose a less complex solution todetect the borders of an object of interest in a sequence of noisyimages.

A viewing system according to the invention as described in the openingparagraph comprises acquisition means for acquiring a sequence ofimages, detection means for detecting an object of interest in saidsequence of images, said detection means comprising:

-   -   localizer detection sub-means for detecting a location of        localizers related to said object of interest,    -   border detection sub-means for detecting a location of borders        related to said object of interest,        and viewing means for displaying said sequence of images.

The viewing system according to the invention comprises detection meansfor indirectly detecting the borders of the object of interest. To thisend, said detection means comprise localizer detection sub-means whichare intended to search for localizers instead of searching for theobject of interest. An advantage is that localizers have been especiallydesigned for being visible in an angiographic image: they are simplyshaped objects made of radio-opaque material, unlike for example a stentor a stenosis which have a low contrast and a complex shape.Consequently, said localizers can be detected easily without involvingcomplex models.

The detection means also comprise border detection sub-means which areintended to find the borders of the object of interest as the mostsalient borders including said localizers. During a procedure of stentplacement for instance, the stent borders are usually more visible thanthe borders of the coronary artery. When the artery borders are searchedfor, some contrast agent may be injected, in order to enhance them.

Therefore, the detection means according to the invention are not verycomplex, thus allowing their implementation in real time.

The viewing system according to the invention further comprisesenhancement means for enhancing the borders of the object of interest,using the location of said borders, and delivering an enhanced sequenceof images. The knowledge of said location allows an outstandingenhancement of the contour of the object of interest. In the domain ofangiography such an outstanding enhancement may help check the stentposition and deployment.

The viewing system according to the invention also comprises measurementmeans for measuring characteristics of said object of interest usingsaid location of borders. An advantage of said characteristics, whichare for instance different widths of the object of interest along itslength, is that they can be used for objectively evaluating for instancethe severity of a stenosis or its reduction by a stent.

The viewing system according to the invention also comprises threedimensional (3D) representation means for representing said object ofinterest in three dimensions. An advantage is that said 3Drepresentation is easily obtained from said object borders and some apriori knowledge of this object. A 3D representation of a tubular objectof interest like a stent or a stenosis may for instance be derived fromthe knowledge of its border location in two views and the assumption ofa cylindrical shape with a variable elliptical section.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be further described with reference to theaccompanying drawings:

FIGS. 1 a, 1 b, 2 a and 2 b illustrate two steps of angioplasty: duringballoon inflation and during stent deployment at the location of astenosis,

FIG. 3 is a functional block diagram of the detection means according tothe invention,

FIG. 4 a is a functional block diagram of the localizer detectionsub-means according to the invention,

FIG. 4 b shows a circular filter for extracting balloon markersaccording to the invention,

FIG. 5 is a functional block diagram of the marker extraction sub-meansaccording to the invention,

FIG. 6 a shows an original angiogram, FIG. 6 b shows two zones ofdetected markers and Fig shows an enhanced object of interest on afiltered background,

FIG. 7 a and 7 b illustrate possible initializations of an activecontour according to the invention,

FIG. 8 a and FIG. 8 b show how an active contour is inflated to matchthe borders of an object of interest,

FIG. 9 shows three possible applications of detecting the borders of anobject of interest: an object enhancement, a measurement ofcharacteristics of the object of interest and a 3D representation of theobject of interest,

FIG. 10 shows a simple 3D model for building a 3D representation of atubular object of int like a stent or an artery,

FIG. 11 describes the local registering means for combining a sequenceof reference images a sequence of enhanced images produced by theenhancement means according to the invei

FIG. 12 is a functional block diagram of a medical examination apparatususing the systems invention.

DETAILED DESCRIPTION OF THE INVENTION

The invention relates to a viewing system and to a method that is usedto actuate the viewing system, for the detection of borders of an objectof interest in real time in a sequence of noisy images. The viewingsystem and the method of the invention are described hereinafter by wayof example in an application relating to the medical field ofcardiology. In said application, the object of interest is an organ suchas an artery or a tool such as a balloon or a stent. These objects areobserved during a medical intervention called angioplasty or PTCA, in asequence of X-ray fluoroscopic images called angiogram.

It is to be noted that the system and method may be applied to anyobject of interest other than a stent or an artery in images other thanangiograms.

Referring to the FIGS. 1 a to 2 b, in the application describedhereinafter the stent implantation is a medical intervention thatusually comprises several steps for enlarging an artery at the locationof a lesion called stenosis. In a preliminary step, the practitionerlocalizes a stenosis 2 in a patient's artery 1in the sequence of images.In a first phase, illustrated by FIG. 1 a, he/she introduces a thinguide wire 3 through the lumen of the artery 1 using a catheter 4. Saidguide wire 3 is extended beyond the stenosis 2. It is to be noted thatsaid guide wire 3 has a radio-opaque tip 9 at its extremity, which helpsthe practitioner check in a sequence of images whether the guide wire 3is properly introduced. A thin tube 5 called a monorail is then easilyslipped onto the guide-wire 3 and placed in the stenosis area. Saidmonorail 5 has a balloon 6 wrapped around it. Said balloon 6 has tworadio-opaque balloon markers 7 and 8 that help the practitioner placethe balloon 6 in the correct position with respect to the stenosis 2.The balloon 6 is then inflated with a high pressure as shown in FIG.. 1b, thus becoming an inflated balloon 10, in order to force the arteryopen. Once the practitioner has checked that the stenosis 2 has beensuitably reduced, the inflated balloon 10 is deflated so as to let theblood flow and the monorail 5 is removed from the artery 2.

In a second phase illustrated by the FIGS. 2 a and 2 b, another monorail11 is introduced into the lumen of the artery 1. Said monorail 11 alsohas a balloon 12 wrapped around it, with two balloon markers 13 and 14,but in addition a stent 15 is put over said balloon 12. The balloon 12is inflated so as to become an inflated balloon 16 and expand the stent15 which thus becomes an expanded stent 17. Then, considering theexpanded stent 17 as a permanent implant, the inflated balloon 16, themonorail 11, the guide wire 3 and the catheter 4 are removed.

It should be noted that the first phase is not compulsory, but oftenperformed by practitioners in order to check in advance whether it ispossible to enlarge the artery before introducing the stent.

As mentioned above, a key point of the intervention is to place thestent properly in the stenosis area. To this end, the practitionervisualizes the area of the stenosis in real time in a sequence of imagesseveral times during the intervention.

According to the invention, the viewing system comprises detecting meansfor detecting an object of interest in said sequence of images. As isshown in the functional diagram of FIG. 3, said detecting means 20comprise localizer detection sub-means 30 for detecting a location oflocalizers related to said object of interest and border detectionsub-means 60 for detecting a location of borders related to said objectof interest A sequence of images IS is presented to said detecting means20. For an image I₀ of said sequence IS said localizer detectionsub-means 30 search for localizers related to the object of interest.Said localizers may have various shapes and be located inside or outsidethe object of interest.

In a preferred embodiment of the invention the object of interest is astent or a stenosis. The problem is that such an object of interest is ahardly radio-opaque object of interest which moves on a movingbackground. Therefore, the stent or the stenosis is preferably detectedindirectly by locating related balloon markers. Said balloon markers aredisposed at each extremity of the balloon. The balloon-markers arerecognizable particularly because they constitute punctual zones,practically black or at least dark in the angiographic images. They arealso very similar in shape. Referring to FIG. 4 a, the localizerdetection sub-means 30 comprise marker extraction sub-means 40 whichperform elementary measures for extracting candidates of markers andforming candidates of couples of markers.

It is to be noted that other types of localizers may be used for thedetection of stent or artery borders. Some stents have their own stentmarkers, which are located on their borders. The tip of the guide wireshown in the FIGS. 1 a to 2 b could also be considered as a singlelocalizer for stenosis border detection during the procedure of tipplacement. As a matter of fact, said tip, which marks the extremity ofthe guide wire, also indicates whether the guide wire has passed thestenosis area or not. Such a procedure of tip placement is rathercritical because of the artery narrowing. Therefore, the detection ofthe stenosis borders during said procedure may help the practitionerpass the guide wire correctly through the stenosis. Said tip may bedetected using ridge enhancement filtering means followed bythresholding means and skeletonization means.

In the preferred embodiment of the invention, the localizers are balloonmarkers. Referring to FIG. 5, the marker extraction sub-means 40comprise several elementary measure sub-means, which are intended tocharacterize the candidates of markers:

First measure means 41 that select punctual dark zones contrasting on abrighter background: This measure is provided by filter means, denotedby F₀. In a preferred embodiment (referring to FIG. 4 b), an appropriatefilter comprises three circular concentric zones, including a centralzone CZ, a dead zone DZ and a peripheral zone PZ. The filter F₀ is alsodivided into n sectoral zones SZ covering 360° and numbered 1 to n. Acurrent sectoral zone Z_(k) is numbered k with 1≦k≦n. The first measureconsists in scanning a current image of the sequence of images in orderto look for a punctual dark zone. A punctual dark zone can be detectedwhen said punctual dark zone is centered in the filter. When a punctualdark zone is centered, it occupies the central zone CZ of the filter andit occupies possibly a part of the dead zone DZ. The first measure isbased on the estimation of contrast of intensity between the centralzone CZ and the peripheral zone PZ. Said estimation of contrast may becarried out by estimating the difference of the average of intensitiesbetween the central zone CZ and peripheral zone PZ. This simple measurewould conduct to a linear estimation of the contrast. In order to refinethe result of this estimation, the first measure is actually carried outby calculating the minimum of the n averages of intensities determinedin the n peripheral sectoral zones separately. These minimum values ofintensities are denoted by:

I_(Pk)=average of intensity in the peripheral sectoral zone numbered k,and I_(CZ)=average of intensities in the central zone CZ.

The final measure provided by the filter F₀ is:$I_{F0} = {{\min\limits_{k}\left( I_{Pk} \right)} - I_{CZ}}$

This measure IF₀ is determined by scanning each pixel of the originalimage I₀ with the filter F₀. It provides an enhanced image, denoted byIZ1, of punctual dark zones, denoted by Z, where all other structureshave disappeared, with the exception of said punctual dark zones thatare now candidates to constitute markers.

Second measure means 42 comprising histogram means denoted by H: in thisimage IZ1, each pixel has a gray level. From the image IZ1, there isconstructed an histogram, which represents the different numbers H ofpixels corresponding to each gray level value G. To the right of theaxis G in FIG. 5, there are the high gray level values and to the leftof the axis G the low gray level values are stated. For each gray levelvalue G, the height H of the box represents the number of pixels to befound having said gray level value. Since the average size of a punctualdark zones Z is determined by the characteristics of the filter F₀, itis possible to estimate the size of a punctual zone in pixels. Assumingthat the size of a punctual zone is p pixels, and assuming that forexample a number z of zones is to be found in the image IZ1, a number ofp.z (p times z) pixels that have the highest gray levels is searched.The histogram H as shown in FIG. 5. permits of accumulating the numberof pixels in adjacent boxes, starting from the right of the axis G,until the estimated number of p.z pixels is reached for the image, i.e.for z zones of p pixels each, while choosing the p.z pixels having thehighest gray levels, i.e. the pixels in the boxes to the right of the Gaxis. The histogram H permits of determining a gray level G_(H), whichyields the p.z pixels.

Third measure means 43 comprising threshold means denoted by T₁; a firstintensity threshold T₁ is then applied to the image IZ1. The thresholdT₁ is chosen equal to the previously determined gray level G_(H). Thatpermits of selecting in the image IZ1 said number p.z of pixels havingat least a gray level equal to G_(H). A new image is formed for whichthe intensities and the coordinates of the pixels are known, thusforming the image of points IZ2.

Fourth measure means 44 called label means which perform a connectivityanalysis on pixels previously selected for the image IZ2, in order toconnect pixels pertaining to a same punctual dark zone Z. The labelingmeans 44 provide a number of labeled punctual dark zones in a new imageIZ3.

Fifth measure means 45 comprising second threshold means T₂: This secondthreshold T₂ is applied, for example, to the intensities of the pixelsof the image IZ3 of labeled zones and to the diameter of the zones inorder to select the best labeled zones. For example, T₂ equals a productof a given intensity and a given diameter, in order to select a numberof remaining punctual zones having the highest intensities and the bestshapes for constituting markers, thus yielding an image of markers IZ4.

Sixth measure means 46 using a table, denoted by CT; this table CT ofpossible couples C1, C2, . . . of selected punctual dark zones isconstructed on the basis of a-priori known distance IM between themarkers, that is with an incertitude of for example 20%. The table CTprovides an image IC of the possible marker couples C1, C2, . . . .

Referring to FIG. 4 a and based on the image IC of possible markercouples, the localizer detection sub-means 30 further comprise coupleextraction sub-means 50 for extracting the best couple of markers basedon criterions among which:

A criterion of distance: the distance between the markers of the bestcouple must be very near the a-priori known distance IM with a givenincertitude.

A criterion of strength: the strength of the best couple must be largerthan the strength of the other couples. The strength of a given couplemay be determined as the average of enhanced intensities yielded by thefilter F₀.

A criterion of similarity: the markers of the best couple must be verysimilar structures. The similarity of the markers of possible couples isdetermined. Once the punctual dark zones Z of p pixels are determined,their centroids are calculated. Small Regions Of Interest, denoted byROI are defined around each centroid, as represented by white squares inFIG. 6 b. For each possible couple correlation is calculated between thecorresponding ROIs. Strong correlation is an indication that the twostrongly correlated ROIs correspond to the markers of a couple ofmarkers.

A criterion of continuous track: the markers of a couple are carried bya monorail, which is guided by a guide wire. The guide wire is more orless visible. However, it may be enhanced by a ridge filter. So, if themarkers of a possible couple are situated on a track corresponding to aridge joining them, this constitutes another indication that the twozones located at the extremities of the continuous track correspond to acouple of markers. Such a continuous track may be qualified byestimating the average ridgeness along the path joining the two zones.The measure of average ridgeness must provide a track that has a shapeas close to the shape of a segment or of a parabola as possible.

The detection of a continuous track connecting the couple of markers maybe performed using a fast marching technique. This technique, well knownto those skilled in the art, first attributes a cost to the pixelslocated in a neighborhood of the couple of markers. Said cost is forinstance inversely proportional to the above calculated ridgeness. Saidtechnique also forms a path between both markers which minimizes a totalcost in a graph made of the pixels of said neighborhood. Hereinafter,said continuous track will be called an inter-marker line IML. It is tobe noted that the guide wire is present on a large portion of the arteryand that consequently the inter-marker line may be detected beyond themarkers.

A criterion of motion: the markers in the coronary artery are movingrapidly with respect to the cardiac pulses. False alarms, that is darkpunctual zones that pertain to the background, are moving much moreslowly with the patient's breathing. In order to eliminate thesepossible false alarms, a temporal difference is formed between twosuccessive images of the sequence. This difference provides a measure oftemporal contrast. The measure of temporal contrast permits of detectingthe dark punctual zones showing an important temporal contrast. Thismeasure is also an indication of a possible couple of markers, sincefalse alarms have a feebler temporal contrast.

All described criterions are combined using a fuzzy logic technique forderiving a composite measure. The higher the composite measure is, thehigher is the probability of the presence of a couple of markers. Thehighest composite measure permits of selecting the best couple ofmarkers from the image of couples IC issued by the marker extractionmeans 1. The coordinates of said markers denoted by (L₁, L₂) in FIG. 4 aand the coordinates of the pixels forming the inter-marker line IML areoutput.

FIG. 6 a shows an original image of a medical sequence representing acatheter, a guide wire, a balloon with balloon markers (as two smalldark points) and an artery on a background of other organs. Thevisualization of the objects of interest (balloon and artery) is verydifficult. Even the balloon markers are hardly visible. FIG. 6 b showsthe original image with zones delimited in white, which are intended forthe determination of the punctual dark zones. In FIG. 6 c, the objectsof interest are enhanced and the background is filtered.

For improving the comfort of the clinician during the intervention, thelocalizers may be temporally registered during the visualization of theimage sequence with respect to the frame of the image, by matchingcorresponding localizers of a current image and of a reference image inthe sequence of images. The localizer registration allows furtherregistering of the objects of interest, which practically do not movewith respect to the localizers. Thus, the object of interest may bezoomed, as shown in FIG. 6 c, without said object being shifted out ofthe image frame. Moreover, temporal filtering means may be used incombination with the means of the invention to further improve theimages of the sequence.

Said image I₀, said marker coordinates (L₁, L₂) and said inter-markerline IML are then processed by the border detection sub-means 60presented in FIG. 3. Said border detection sub-means 60 aim at derivingthe borders of the object of interest from the knowledge of thelocalizer's location (L₁I, L₂). In the preferred embodiment of theinvention, this may for instance be carried out by an active contourtechnique (also called “snake”). This technique, well known to thoseskilled in the art, first of all consists in defining an initial contourand secondly in making said initial contour evolve under the influenceof internal and external forces. To this end said border detectionsub-means 60 comprise initialization sub-means 61 and active contoursub-means 62 as shown in FIG. 3.

As shown in FIG. 7 a, said initialization sub-means 61 may use themarker locations (L₁, L₂) to derive an elliptical initial contour EICdefined by a major axis MA equal to a distance between markers L₁ and L₂and called an inter-marker distance IMD and a minor axis mA equal to apercentage of said inter-marker distance IMD.

If the artery is curved, it may be more realistic (as shown in FIG. 7 b)to take as an initial contour a contour RIC of a rubber band RB havingthe inter-marker line as a medial axis. Said initial contour EIC or RICis then used as a starting position for an active contour AC, shown FIG.8 a, which is deformed by said active contour sub-means 62. A dynamic ofthe active contour AC is given by a law of motion. The deformation ofsaid active contour AC implies two types of forces, which are applied ateach point of the active contour AC on a normal to said contour:

-   -   external forces FE, that constrain the active contour AC to        stick to the borders of the object of interest. They are for        instance related to the above-calculated ridgeness of the stent        borders. A strength of said external force {right arrow over        (F)}_(E) is determined by the highest ridgeness encountered on        the normal {right arrow over (N)} to the active contour AC at a        given point P,    -   internal forces {right arrow over (F)}_(I) that represent        regularization forces, that constrain the active contour AC to        be smooth. They are usually based on curvature constraints.

It is to be noted that the inter-marker line IML has a non-negligibleridgeness due to the guide wire contrast. Said ridgeness may causeparasitic external forces that have to be eliminated, in order toprevent the active contour from being attracted by said inter-markerline IML. This is done easily since the location of said inter-markerline is well known. When said external and internal forcescounterbalance each other, said active contour AC stops in a finalposition, which is the location of the borders BL of the object ofinterest as shown in FIG. 8 b.

In a second embodiment of the invention, the viewing system (as shown inFIG. 9) also comprises enhancement means 70 for enhancing said bordersusing said location of borders BL and for delivering an enhancedsequence of images EIS. Since said location of borders BL is known, theborders of the object of interest are enhanced very easily. Said bordersare formed by points that have a gray level value. Said enhancementmeans 70 simply consist in increasing said gray level values so as tomake the borders more visible. An outstanding enhancement is thusobtained and the main issue is to tune the enhancement so as to keep theenhanced sequence of images EIS acceptable for the practitioner.

In a third embodiment of the invention, the viewing system (as shownFIG. 9) also comprises measurement means 71 for measuringcharacteristics CM of said object of interest using said location ofborders BL. An interesting characteristic measure of a tubular objectlike a stent or an artery is a collection of widths of said objectmeasured at several locations along a length of said object, forinstance along said inter-marker line IML for a stent or along the tipfor a stenosis. Variations of said widths may indicate whether thestenosis has been properly reduced or whether the stent has beenproperly expanded.

It is to be noted that the invention is not limited to width measures.The knowledge of the stent or of the artery borders also enables forinstance an estimation of an agent contrast flow in the stenosis area tobe derived, by measuring the mean contrast of contiguous sections of theartery at different times.

In a fourth embodiment of the invention, the viewing system (as shownFIG. 9) also comprises 3D representation means 72 for delivering athree-dimensional (or 3D) representation 3DR of said object of interestusing said location of borders BL. Such a 3D representation of a tubularobject of interest, like an artery or a stent is easily obtained fromtwo views (I₀, I₀′), which are preferably orthogonal views of saidtubular object. It is not an issue in the domain of angiography, wherean X-ray C-arm medical examination apparatus may provide two views indirections perpendicular to the axis of the tubular object andperpendicular to each other. It is also to be noted that very littledistortion is introduced since the patient is placed at the center ofthe medical examination apparatus.

The localizers (L₁, L₂, L′₁, L′₂) detected in each sequence of imagesare matched and define a 3D referential in which all the points of theborders of the object of interest may be positioned in 3D. It is thenpossible to obtain 3D measurements of the object of interest and 3Dvisualizations. In particular, if the geometry of the object of interestis known or if a 3D model is available, it is possible to fit said modelto the border points and object characteristics so as to obtain arealistic 3D viewing of the object of interest. In the domain ofangiography, a 3D model like a cylindrical shape with a circular or anelliptical section may be used for a 3D representation of a stent or anartery (as shown in FIG. 10). Said 3D representation may offerinformation about the stent placement or the stent bending for instance.

A sequence of reference images, also called peri-interventional images,is usually acquired before the intervention with an injection of acontrast agent, which makes arteries visible. Said sequence of referenceimages, therefore, comprises features like the artery borders, whichhelp the practitioner to locate and assess a stenosis before startingthe procedure of stent placement. During the procedure of stentplacement, contrast agent is generally not injected and, consequently,the artery and stenosis borders are usually visible neither in the imagesequence IS nor in the sequence of enhanced images EIS provided in realtime by the viewing system according to the invention. A way ofimproving the accuracy of the visualization is to provide thepractitioner with the features of the sequence of reference imagesduring the procedure of stent placement.

In a fifth embodiment of the invention, the viewing means thereforecomprise local registration means 80 for registering said sequence ofreference images or part of it with respect to said sequence of enhancedimages EIS so as to form a new sequence of enhanced images, in whichsaid sequence of reference images and said sequence of enhanced imagesare combined.

The sequence of enhanced images EIS output by the enhancement means 70is a live sequence, which will be denoted by EIS(t) hereinafter. Thesequence of reference images RIS(n) is a stored sequence, comprising anumber n of images. Referring to FIG. 11, both sequences are entered inthe local registration means 80. A reference image RIS(n₀) is registeredusing for instance a block-matching technique. Gray level values of saidreference image RI are combined with the gray level values of thecorresponding enhanced image EI(t₀) using for instance an α-blendingtechnique. The correspondence between no and to can be evaluated throughthe compensation of the respiratory and heart motions. A new enhancedimage NEI(t₀) is output, in which the features of the reference imageRI(n₀), like the borders of the artery are seen through the enhancedimage EI(t₀).

It should be noted that the sequence of enhanced images EIS(t) can aswell be registered with respect to the sequence of reference imagesRIS(n) so as to provide a new sequence of reference images NRIS(n) (asshown in FIG. 11). In said new sequence of reference images enhancedfeatures of an enhanced image EI(t₀), like the stent borders, are madevisible through the corresponding reference image RI(n₀).

FIG. 12 shows the basic components of an embodiment of an image viewingsystem 150 in accordance with the present invention, which isincorporated in a medical examination apparatus. As indicatedschematically in FIG. 11, said medical examination apparatus hasacquisition means 151 for acquiring a sequence of images IS. Saidsequence of images IS is processed by a processing device 153 comprisingdetection means as described above. The image viewing system 150 isgenerally used in the intervention room or near the intervention roomfor the processing of real time images. Should steps of the presentmethod be applied to stored medical images, for example for estimatingmedical parameters, the system for processing the data of the storedimages would be called an image viewing station. The medical examinationapparatus provides the image data IS via a connection 157 to theprocessing device 153. Said processing system 153 provides processedimage data to display and/or storage means. The display means 154 may bea screen. The storage means may be a memory MEM of the processing system153. Said storage means may alternatively be external storage means.This processing device 153 may comprise a suitably programmed computer,or a special purpose processor having circuit means such as LUTs,Memories, Filters, Logic Operators, that are arranged to perform thefunctions of the steps of the method according to the invention. Theimage viewing system 150 may also comprise a keyboard 155 and a mouse156. Icons may be provided on the screen to be activated by mouseclicks, or special pushbuttons may be provided on the system, toconstitute control means 158 for the user to start, to control theduration or to stop the processing means of the system at selectedinstants.

The present invention is not limited to two-dimensional image sequences.As already mentioned above, a volume of angiographic data, comprisingseveral views of a region of interest of the human body at a same timet, may be acquired by an X-ray C-arm medical examination apparatus. Thedescribed processing steps may be applied to each view produced at thetime t.

The present invention is applicable regardless of the medical imagingtechnology that is used to generate the initial data. Variousmodifications can be made to the order in which processing steps areperformed in the described specific embodiment. The described processingsteps applied to medical image data can advantageously be combined withvarious other known processing/visualization techniques.

The drawings and their description hereinbefore illustrate rather thanlimit the invention. It will be evident that there are numerousalternatives, which fall within the scope of the appended claims. Inthis respect the following closing remarks are made: There are numerousways of implementing functions by means of items of hardware orsoftware, or both. In this respect, the drawings are very diagrammatic,each representing only one possible embodiment of the invention. Thus,although a drawing shows different functions as different blocks, thisby no means excludes that a single item of hardware or software carriesout several functions, nor does it exclude that a single function iscarried out by an assembly of items of hardware or software or both.

Any reference sign in a claim should not be construed as limiting theclaim. Use of the verb “to comprise” and its conjugations does notexclude the presence of elements or steps other than those stated in aclaim. Use of the article “a” or “an” preceding an element or step doesnot exclude the presence of a plurality of such elements or steps.

1. A viewing system, comprising acquisition means for acquiring a sequence of images, detection means for detecting an object of interest in said sequence of images, said detection means comprising: localizer detection sub-means for detecting a location localizers related to said object of interest, border detection sub-means for detecting a location of borders related to said object of interest, using said location of localizers, and viewing means for displaying said sequence of images.
 2. A viewing system as claimed in claim 1, wherein said border detection sub-means comprise: initialization sub-means for building an initial contour of said borders, containing said localizers, from a priori knowledge about said object of interest, active contour sub-means for moving said initial contour under the effect of forces related to said object of interest within said sequence of images.
 3. A viewing system as claimed in claim 1, comprising enhancement means for enhancing said borders using said location of borders and delivering a sequence of enhanced images.
 4. A viewing system as claimed in claim 1, comprising measurement means for measuring characteristics of said object of interest using said location of borders.
 5. A viewing system as claimed in claim 4, wherein said characteristics are widths of said object of interest along a length of said object of interest.
 6. A viewing system as claimed in claim 1, wherein said acquisition means are able to acquire at least two views of said object of interest, said viewing system also comprising 3D representation means for delivering a 3D representation of said object of interest from said views and said location of borders.
 7. A viewing system as claimed in claim 6, wherein a cylindrical model is used by said 3D representation means when said object of interest has a tubular shape.
 8. A viewing system as claimed in of claims 1, wherein said object of interest is a stenosis or a stent and said localizers are a tip (9) or balloon markers.
 9. A viewing system as claimed in claim 3, wherein said viewing means also comprise local registering means for registering a sequence of reference images with respect to said sequence of enhanced images so as to form a new sequence of enhanced images, in which said sequence of enhanced images and said sequence of reference images are combined.
 10. A viewing system as claimed in claim 3, wherein said viewing means also comprise local registering means for registering said sequence of enhanced images with respect to a sequence of reference images so as to form a new sequence of reference images in which said sequence of enhanced images and said sequence of reference images are combined.
 11. A method, comprising a detection step for detecting an object of interest in a sequence of images, said detection step comprising sub-steps of: localizer detection for detecting a location of localizers related to said object of interest, border detection for detecting a location of borders related to said object of interest, using said location of localizers.
 12. A device comprising detection means for detecting an object of interest in a sequence of images, said detection means comprising: localizer detection sub-means for detecting a location of localizers related to said object of interest, border detection sub-means for detecting a location of borders related to said object of interest, using said location of localizers.
 13. A computer program comprising a set of instructions for implementing a method as claimed in claim 11 when said program is executed by a processor.
 14. A medical examination imaging apparatus comprising a viewing system as claimed in claims
 1. 